In a microelectronics manufacturing process, a semiconductor wafer is processed through a series of tools, which form lithographic patterns, deposit films, implant dopants, and/or measure physical and/or electrical characteristics of the formed structures. Such processing procedures have broad industrial applications, including but not limited to, semiconductors, flat-panel displays, MEMS (Micro-Electro-Mechanical Systems), and disk heads.
Generally, each tool is operated by a program, hereafter referred to as a “recipe”, which contains all conditions and instructions necessary to process a wafer. For example, a typical lithography recipe may contain information about the location of exposure fields, alignment strategies, and dosages. A typical Reactive Ion Etch (RIE) recipe may contain information about gas flow rates and etch times. A typical metrology recipe may contain information about locations of targets to be sampled, data acquisition conditions, and desired analyses. As tools become more and more advanced, they require more complicated quality recipes that are out of the reach of average users. In addition, as the technology size/node decreases, recipe complexity and the number of recipes increase exponentially. As a consequence, many recipes are not optimized as required.
As a wafer moves through a manufacturing process, in addition to the aforementioned recipe failures, machine/hardware/tool failures may also occur. As equipment becomes more sophisticated, there are more chances that something may go wrong without being detected. Failures that occur during an actual processing may lead to yield degradation, while failures that occur during a test may increase the time needed to build a fully functioning chip, and may provide faulty feedbacks to processing sectors, which in turn may lead to yield degradation.
In a real system, a broad category of failures may be generated by various parts of the system. For example, in the Semiconductor Industry, the Semiconductor Equipment and Materials International, Inc (SEMI) standards dictate that a broad category of failures, known as S5F1 messages, hereafter also referred to as alarms, are to be sent to the host. Hundreds to thousands of these alarms may be generated by a single tool each week. In a processing system with hundreds of tools and tens of thousands of recipes, it is important to have the capability to analyze the entire volume of alarms, to separate the important alarms from noise, and to identify areas for improvements for each toolset. The state-of-the-art technologies do not provide a satisfactory solution to this problem.
Based on the above, there is a need in the art to determine a root cause for alarms generated in a processing system.